BRPI0711282B1 - METHODS FOR DETERMINING TIME-DEPENDENT CHANGES IN THE HYDROCARBON CONTENT OF A SUB-SURFACE RESERVOIR - Google Patents

Description

(54) Title: METHODS FOR DETERMINING TIME-DEPENDENT CHANGES IN THE HYDROCARBON CONTENT OF A SUB-SURFACE RESERVOIR (51) lnt.CI .: G01V 3/12; G01V 3/08 (30) Unionist Priority: 05/04/2006 US 60/797560 (73) Holder (s): EXXONMOBIL UPSTREAM RESEARCH COMPANY (72) Inventor (s): LEONARD J. SRNKA; JAMES J. CARAZZONE; DIMITRY A. PAVLOV (85) National Phase Start Date: 11/03/2008

1/28 “METHODS FOR DETERMINING TIME-DEPENDENT CHANGES IN THE HYDROCARBONET CONTENT OF A SUB-SURFACE RESERVOIR” [0001] This claim claims the benefit of the provisional U. S. 60 / 797,560 requested on May 4, 2006.

FIELD OF THE INVENTION [0002] This invention generally relates to the field of geophysical prospecting, and, more particularly, to electromagnetic surveys from a controlled source typically in offshore environments, where a controlled electromagnetic transmitter is towed above, or positioned between receivers electromagnetic fields on the seabed, for the purposes of research, development, and hydrocarbon production. Specifically, the invention is a method for determining the difference between the electrical resistivity of an underground reservoir in an initial moment, and its electrical resistivity in one or more moments later, and relating this difference to the production of hydrocarbons in the reservoir during the intermediate period. .

BACKGROUND OF THE INVENTION [0003] This invention addresses the problem of determining the three-dimensional (3D) distribution of hydrocarbon fluids within an underground reservoir, which will often be located under a body of water, as under the sea, during the period of time (or periods) of hydrocarbon production in that reservoir. Applications of seismic methods to these problems are called time-lapse or 4D methods. A critical problem for the production of hydrocarbons (gas, gas condensate and oil) in reservoirs is the exact knowledge of the distribution of hydrocarbon saturation within the porous rocks that comprise the reservoir. When hydrocarbons are produced from the reservoir, the hydrocarbon saturation decreases and, the water saturation increases in a non-uniform manner, within the reservoir. Although seismic methods have been developed for 4D applications to monitor reservoir fluids, these methods are expensive, and are often ineffective due to sensitivity

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2/28 relatively low seismic response to changes in hydrocarbon saturation. This low sensitivity is particularly true for oil reservoirs, due to the acoustic properties of most oils being very similar to those of the reservoir forming waters and, therefore, changes in oil saturation are not reflected in the seismic response.

[0004] Other methods are known in the art to evaluate the properties of reservoir fluid. Resistivity and hydrocarbon saturation data are available during reservoir depletion, using methods for drilled wells (inside the borehole or well profiling), within a few meters of the drilled well. However, well profiling methods are not effective between wells that are generally spaced hundreds to thousands of meters apart, as found in many hydrocarbon fields, due to the limited penetration distance of probe signals into the reservoir, from of a well profiling device, inside the hole. In addition, production wells are generally wrapped with electrically conductive coating, which severely limits the use of electrical methods to monitor the resistivity of the reservoir fluid, since the reservoir is shielded from the electrical probe signal by the coating (except in very low frequency).

[0005] Reservoir resistivity and saturation data are also available during reservoir depletion from cross-drilled well methods (cross wells), using seismic or electromagnetic energy (c. Rector, WJ (ed.), Crosswell Methods : Special Issue, Geophysics 60, No. 3 (1995)). However, cross-well methods require at least: two wells to be used simultaneously for measurement, which is expensive, since production from both wells must be stopped and the production pipeline must be removed from the wells. In addition, cross-well data comes primarily from two-dimensional measurements in the common vertical plane that connects the measurement wells. Most wells in subsea reservoirs are spaced from the vertical, which limits the amount of vertical plane common between pairs of wells. Cross-well methods are also not effective between wells that are,

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3/28 generally spaced from hundreds to thousands of meters apart, as found in many hydrocarbon fields, due to the limited penetration distance of the source's probe signals into the bore. And, similar to the case of single-well profiling, the presence of electrically conductive coating in production wells severely limits the ability to use cross-well electrical methods to detect the resistivity of the reservoir fluid. [0006] Another method that is used routinely to assess fluid saturation between wells is the mathematical simulation of fluid flow from the reservoir. However, the reservoir simulation necessarily incorporates many simplifications and assumptions about the properties of rocks between the wells, in order to make the mathematical simulation practical, even on a large computer. Reservoir simulation also requires continuous adjustment of numerical parameters in the model, to match the data measured in the wells, the so-called historical combination approach, and these parameters may not have a simple connection to the measured properties of rock and liquid .

[0007] Results of off-shore controlled source electromagnetic surveys (CSEM) such as those collected using the methods presented in US patent 4,617,518 to Srnka and in US patent 6,603,313 referred to previously and US patent publication 2003/0050759, showed that the gross resistivity of fluids in hydrocarbon reservoirs can be determined remotely. For a good first approximation, marine CSEM data obtained using a horizontal electric dipole (HED) source, are primarily sensitive to the vertical net resistance (gross resistivity x net vertical thickness) of the underground reservoir (Kaufman and Keller, Frequency and Transient Soundings, 300-313, Elsevier (1983)). An offshore survey in West Africa, (Eidesmo, et al, First Break, 20, 144-152 (2002); Ellingsrud et al., The Leading Edge, 972-982 (2002)) confirmed that subsurface resistivity caused by presence of hydrocarbons can be detected.

[0008] It is well known that terrestrial electrical resistivity can be anisotropic. See, for example, Keller and Frischnecht, Electrical Methods in

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4/28

Geophysical Prospecting, 33-39, Pergamon (1966); Kaufmann and Keller, Frequency and Transient Soundings, 257-284, Elsevier, N.Y. (1983), Negi, et al., Anisotropy in Geoelectromagnetism, Elsevier, N.Y. (1989); and Zhdanov and Keller, The Geoelectrical Methods in Geophysical Exploration, 119-124; Elsevier, N.Y. (1994). Several publications teach how to calculate (model) the anisotropic electrical responses of the earth to various controlled sources: See, for example, Chlamtac and Abramovici, Geopfysics 46, 904-915 (1981); Yin and Weidelt, Geophysics 64, 426-434 (1999); Yin and Maurer, Geophysics 66, 1405-1416 (2001). Several authors also discuss the interpretation of azimuth electrical anisotropy (for example, Watson and Barker, Geophysics 64, 739-745 (1999); and Linde and Peterson, Geophysics 69, 909-916 (2004)). Others discuss the interpretation of anisotropy (Jupp and Vozoff, Geophys. Prospecting 25, 460-470 (1977); Edwards, et al., Geophysics 49, 566-576 (1984); and Christensen, Geophys. Prospecting 48, 1-9 (2000)) from acquired data, using a variety of controlled electromagnetic sources.

[0009] US patent 6,739,165, to Strack, discloses a method for monitoring changes in the electrical resistivity of a reservoir by measuring changes in data from the electric and magnetic fields on the earth's surface, due to excitations by controlled inductive and galvanic sources and by natural magnetoteluric sources, which must include measurement of resistivity changes in at least one well drilled that penetrates the reservoir. Strack does not disclose the use of imaging or inversion to map the distribution of gross reservoir resistivity p _r Sh _C or hydrocarbon saturation, and does not explain the electric anisotropy.

[0010] Johnstad, et al., In patent application _: WO 2004/086090, discloses a method for monitoring reservoir resistivity similar to that of Strack, but which includes an electromagnetic source for the interior of the bore that is constructed by transmitting electrical energy from the seabed, into the reservoir, through the electrically conductive coating that lines the well. The authors do not disclose the use of 3D imaging or 3D inversion to determine p _r or Shc,

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5/28 and does not reveal how to include the effects of electrical anisotropy.

[0011] Constable, in patent publication WO 2004/053528 (2004), al., Explains a method for monitoring hydrocarbon reservoirs in real time. He proposes to use several sources of vertical and horizontal electric dipoles and natural electromagnetic sources (for example, magnetoteluric), alone or in combinations, together with antennas on the seabed containing electrical and magnetic sensors in various arrangements, distributed over an area containing a hydrocarbon reservoir. Antennas on the seabed can be permanently attached to the seabed or can be positioned separately at different times. The Constable's method for monitoring time changes in gross resistivity p _r of the reservoir consists of measuring the earth 's electric impedance for each combination of source-receiver using the two electric field components, horizontal and vertical orthogonal, the receiver signals that respond to the transmitter's energy, and map these impedances over the reservoir area. Magnetoteluric data can optionally be used to help determine the electrical background (volume of the earth's non-reservoir). No mathematical inversion or image formation of the receiver signals, of any dimensionality and any method to include the effects of anisotropy are presented.

[0012] Loke (Constrained Time-Lapse Resistivity Imaging Inversion, EEM-7 communication, Proceedings of the SAGEEP Symposion, Denver, March 3, 2001) describes the use of 2D forced image inversion to measure changes in resistivity time subsurface for environmental applications. Loke presents the use of the resistivity inversion result obtained at the beginning of the survey as an initial model for the resistivity inversion performed at a later time, in order to reduce artifacts in the result that can be introduced by other effects besides changes in the subsurface resistivity, such as changes in the acquisition system. This publication limits its explanation to DC resistivity surveys, and uses an example of data obtained from a terrestrial Wenner-Schlumberger array, a survey method

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6/28 well known to practitioners of the technique. Anisotropic effects are not explained by Loke, nor does he explain offshore data, the use of multiple components of the data, or applications for hydrocarbons.

[0013] Gasperikova, et al., (A Feasibility Study of Geophysical Methods for Monitoring Geologic CO2 Sequestration, Extended Abstract RC 3.8, SEG Annual Meeting, Denver, Colorado, October 2004) explains the use of terrestrial electric field measurements associated with excitation by a grounded HED source, to measure the change in water saturation (or 1 - Sh _C ), in the Schrader Bluff field, in Alaska's North Slope, as a consequence of CO2 injection based on 3D frontal modeling. Time-dependent changes are simulated by differentiating frontal model calculations at appropriate times. The work presented does not describe which electric field components are optimal for this measurement, nor are any anisotropic effects discussed.

[0014] Hoversten, et al. (Direct Reservoir Parameter Estimation using Joint Inversion of Seismic AVO and marine CSEM Data, Extended Abstract RC 2.1, SEGS Annual Meeting, Denver, Colorado, October 2004) presents a method for simultaneous 1D (flat stratified land) inversion of data (HED source ) of seismic reflection and marine CSEM from the seabed. The CSEM data is restricted to the data connected in line of the electric field (ie, source line over Ex, see figure 1). Hoversten et al. (2004) does not teach time-lapse methods for monitoring the reservoir, nor does it teach how to include terrestrial electrical anisotropy in inversions.

[0015] Consequently, there is a need for a method to directly estimate the hydrocarbon saturation across the entire reservoir in a 3D sense, remotely measuring and converting a subsurface physical parameter that is highly sensitive to this saturation, and that can repeat this measurement / image formation, and analyze the data, when the reservoir fluids are produced: This method should consider resistivity anisotropy. The present invention satisfies this need.

SUMMARY OF THE INVENTION

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7/28 [0016] In one embodiment, the invention is a method for determining time-dependent changes in the hydrocarbon content of an underground reservoir from electromagnetic survey data from a controlled source obtained from the subsurface region containing the reservoirs , the mentioned method comprising:

(a) obtain electromagnetic field data recorded in a plurality of receiver locations, both online and offline (in relation to a survey source line), from an initial survey of the subsurface region, and corresponding survey results from at least a later survey of the same region conducted under substantially the same conditions, said data comprising a sensitive field component, at least predominantly, to vertical resistivity, and a sensitive field component, at least predominant, to horizontal resistivity;

(b) for each survey, solve Maxwell's electromagnetic field equations for horizontal resistivity and vertical resistivity in a plurality of positions (x, y, z) in the underground reservoir, using survey acquisition parameters and electromagnetic data from measured fields; and (c) compare the results of calculated resistivity between the surveys.

[0017] The saturation values of the hydrocarbon fluid can be calculated from the horizontal and vertical resistivities using Archie's law, or another relation, and comparison of results converted into image for this parameter, between surveys separated in time, provided that a basis for analysis changes when hydrocarbons from the reservoir are produced over time.

BRIEF DESCRIPTION OF THE DRAWINGS [0018] The present invention and its advantages will be better understood

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8/28 with reference to the following detailed description and the accompanying drawings, in which: [0019] Fig. 1 illustrates a survey geometry suitable for an embodiment of the present invention, in which both the horizontal, electrical and magnetic sources, they are used in combination with a plurality of electromagnetic receivers of multiple components located, both online and offline;

[0020] Fig. 2 illustrates a survey geometry and a subsurface resistivity model for a model calculation to provide a test example of the method of the present invention;

[0021] Fig. 3A shows Ex line amplitude, and Fig. 3B shows Ex phase, for an HED source and for EVTI variable values, with and without a resistive layer in the model of Fig. 2;

[0022] Fig. 4 illustrates an in-depth simulated image of the vertical resistivity of an underground hydrocarbon reservoir model, averaged over the reservoir thickness, obtained by 3D inversion of electromagnetic data from the E _x seabed in line and H _z offline, obtained in an initial moment, in the survey geometry shown in Fig.2;

[0023] Fig. 5 illustrates an in-depth simulated image of the vertical resistivity of an underground hydrocarbon reservoir model, averaged over the reservoir thickness, obtained by 3D inversion of electromagnetic data from the Ex seabed in line and Hz offline, obtained at a later time in the survey geometry shown in Fig.2, in which measurements of the seabed are acquired in the same locations using the same source lines as the first time; and [0024] Fig. 6 is a flow chart showing the basic steps in an embodiment of the method of the present invention.

[0025] The invention will be described in connection with these preferred embodiments. However, to the extent that the following detailed description is specific to an embodiment, or a particular use of the invention, it is intended to be illustrative only and should not be construed as limiting the scope

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9/28 of the invention. On the contrary, it is intended that it covers all alternatives, modifications and equivalents that may be included within the spirit and scope of the invention, as defined by the attached claims.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS [0026] The invention is a method for determining time-dependent changes in vertical and horizontal electrical resistivities within a subsurface region off the coast, such as a hydrocarbon reservoir, due to changes in the reservoir properties, like fluid saturation in the pores of the rock. One cause of these changes is the extraction, or intentional injection of fluids, as performed in the production of hydrocarbons. The invention requires measurements of controlled source electromagnetic survey (CSEM) data at an initial time and at one or more moments later for at least one in-line electromagnetic field component and at least one offline component, the selection of particular components depending on the type of source. The invention makes use of the knowledge that certain components of electromagnetic fields are predominantly, or almost exclusively, sensitive to vertical resistivity or horizontal resistivity, but not both, while other field components are sensitive to both resistivities. The invention also makes use of the knowledge that changes in fluid saturation in a hydrocarbon reservoir will change both resistivity, vertical and horizontal, within the reservoir, since reservoirs predominantly contain internal stratifications and other structures and, therefore, , generally exhibit vertically transverse electrical isotropy (EVTI). Since the thickness of the reservoir is generally small compared to the depth of the reservoir cover, it is understood in this invention that the vertical resolution of EVTI, within the reservoir range, will be substantially less than the thickness of the reservoir. This smaller spatial resolution within the reservoir is a consequence of the fact that frequencies from low electromagnetic sources, typically less than 1Hz, have to be used to penetrate to the depth of the reservoir, due to the electromagnetic effect of depth of

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10/28 skin, quite known. It follows that the frequencies required for greater spatial resolution, within the thinnest reservoir, are typically absent in the remotely measured reservoir response data, since these higher frequencies penetrate only much less than the depth of the reservoir.

[0027] Recent developments in marine electromagnetic controlled source survey (CSEM) now provide the means to remotely determine the resistivity of an underground reservoir using iterative frontal modeling or mathematical inversion (Srnka, Remote Reservoir Resistivity Mapping, Society of Exploration Geophysicists 75th Annual Meeting Extended Abstracts, Houston, November 2005, work presented SS 3.3). Srnka, et al. (Remote Reservoir Resistivity Mapping - Breakthrough Geophysics for the Upstream Abstract 17284, Offshore Technology Conference, Houston, Texas, May 2005) additionally showed that the magnitude of the expected CSEM response from a different hydrocarbon reservoir off the coast of Africa Western, it combined, very closely, with the predicted response of a realistic three-dimensional computer model of the earth's electrical structure, when the presence of electrically resistive hydrocarbons in the reservoir was considered.

[0028] Electromagnetic surveys from controlled sources offshore, such as those collected using the methods presented in US patent 6,603,313, to Srnka and, US patent publication 2003/0050759, published on March 13, 2003, (Srnka, et al.), showed that resistivity on earth can be strongly dependent on the direction of the flow of the electric current used to make these measurements. In particular, the vertical electrical resistivity p _v can be much higher (two or more times) than the horizontal electrical resistivity Ph, especially in finely stratified rocks such as shales, and can vary, in magnitude, from position to position. This phenomenon is called electrical anisotropy or, specifically, vertical vertical electric isotropy (EVTI) by practitioners of the technique. The electrical resistivity of the earth can also vary azimuthally (ie,

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11/28 in compass directions), but this anisotropic effect appears to be generally much less important (ie, of much smaller magnitude) than EVTI in sedimentary basins of interest for hydrocarbon research.

[0029] The presence of EVTI distorts the signals received at the electromagnetic receivers of the seabed used in marine MSEM surveys, acquired with a controlled source of horizontal electric dipole (HED), or horizontal magnetic dipole (HMD), in relation to those that would be received in the absence of EVTI. See Fig. 1 for an illustration of the survey geometry appropriate for the present invention. The drawing shows a lifting vessel 1 towing an HED 2 and an HMD 3 on the seabed 4, in which in-line receivers 6 and out-of-line receivers 7 are arranged in a stationary arrangement on the source 5 tow cable. This distortion affects the interpretation of the marine CSEM resistivity anomalies associated with the presence of hydrocarbons contained in a reservoir, as in 8. These distortion effects appear in both, amplitude and phases of measured fields of the seabed, and change with frequency . These distortions can mask the presence of hydrocarbons (false negatives.) Or incorrectly suggest their presence (false positives). Such distortions have been observed in numerous CSEM surveys. For example, Tompkins et al., (Effects of Vertical Anisotropy on Marine Active Source Electromagnetic Data and Inversions EAGE 65th Annual Convention, Paris, France, abstract. E025 (2004)) describe several effects of EVTI on marine CSEM data collected for applications hydrocarbon, using only electric field measurements (seabed). These effects include underestimating the true depth for underground formations such as hydrocarbon reservoirs and underestimating their gross resistivity if EVTI is neglected.

[0030] Srnka (PCT patent publication W02006 / 13550) teaches how to measure and analyze EVTI in marine CSEM surveys. The analysis steps presented here include: (1) measurements of data from appropriate electric and magnetic fields on the seabed. online and offline, whose exact combination

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12/28 depends on the type of controlled electromagnetic source (HED or HMD) being used; and (2) mathematical inversion of sea bed data for the subsurface electrical resistivity structure, including the EVTI effect, using a numerical algorithm on a computer.

[0031] To use these principles, the CSEM source needs to produce both vertical and horizontal currents. Two types of marine CSEM sources do this, the horizontal electric dipole (HED) and the horizontal magnetic dipole (HMD). Preferred embodiments of the invention employ particular electromagnetic field measurement data required for each of the two types of sources, as taught by the PCT patent publication W02006 / 135510 Figs. 1, 2 and 3A-B. of this application are all reproduced from this previous application.

[0032] In certain cases, the resistivity anisotropy in the subsurface region covered by the survey, including the underground reservoir, may be very small (that is, EVTI almost equal to the unit). This can occur if the reservoir is a very uniform sandstone deposit and the subsurface region outside the reservoir does not contain a significant volume of isotropic shale deposits. In these few cases, the CSEM responses will be approximately isotropic, which can be readily determined by analyzing the survey data, as taught in the prior art. In these cases, the mathematical inversion of the data can be performed using few measured data components that are sensitive to the reservoir resistivity (for example, only EX. In line) and using an isotropic inversion algorithm for more efficient and economical image formation subsurface region.

[0033] Fig. 1 illustrates a possible data acquisition geometry (survey) for the case of terrestrial resistivity, generally anisotropic (that is, EVTI> 1). A vessel 1, at or below the sea surface, tows a source of HED 2 and / or a source of HMD 3, near the seabed 4, along the source line 5, and transmits a specified waveform of electric current as is usually done (usually with HED source) in the CSEM survey. Alternatively, the source of HED and / or HMD can be positioned on a

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13/28 stationary way near, or in contact with the seabed, between each pair of individual electromagnetic receivers in line 6, from the seabed, along line 5, when transmission of the source waveform occurs. The choice of using a continuously towed and / or stationary source depends on a variety of operating conditions for the survey, but primarily on the electromagnetic noise environment. Both, source and natural noise, increase when the water depth decreases, favoring the use of stationary sources in shallow water (typically 150 m or less) so that very long data summing (stacking) times can be used without lateral data misalignment to suppress random noise. The transmission of the source waveform may consist of a variety of waveforms of appropriate duration, such as those described in PCT patent publication W02005 / 117326, or, more generally, in the publications previously referred to. Offline receivers 7 record the electromagnetic response of the earth due to the excitation of the source, simultaneously with the response being measured by the receivers in line 6. The source line, receivers in line and, receivers off line are placed on the seabed above, and in the vicinity of underground geological formations 8, within the soil that has been identified as potential reservoirs for hydrocarbons or other resources. Seabed receivers are positioned at various distances from the source of HED or HDM, using uniform or non-uniform interreceptor spacing (or both), as determined by pre-survey modeling of anticipated seabed responses, or by limitations operational, as will be well understood by practitioners of the technique. Typically, the in-line and transverse clearances of the receivers are 500 to 5000 m.

[0034] With electromagnetic data acquired as described above in the first moment of the survey, the PCT patent publication previously referred to W02006 / 135510, allows the terrestrial resistivity values, including EVTI, to be determined in the region covered by each combination of receiver in online and offline survey, using one or more methods of data analysis and interpretation. The quantity, depth, and distributions

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14/28 sides of any EVTI present are determined from analysis of field responses, both online and offline, at the available survey frequencies, the highest frequency determining EVTI at the shallowest depth (starting at the seabed and extending down by approximately one EM skin depth), and the lowest frequency providing the integrated effects of EVTI, from shallower depths, to greater depths of effective penetration (approximately half the diffuse EM wavelength, or times the depth electromagnetic skin). This determination allows the effects of EVTI to be removed from, or considered in, seabed CSEM data, so that an accurate prognosis of reservoir resistivity (ie resistivity of a buried underground reservoir formation) can be performed. [0035] When the survey described in Fig. 1 is acquired at one or more moments later, in order to determine time-dependent changes in subsurface resistivity, the survey geometry is preferably substantially similar to that used for the survey in the first survey moment, so that the measured data represent the terrestrial electromagnetic responses for the same subsurface regions. In practice, experiments with marine CSEM surveys show that the positions of the receivers, for surveys at a later time, must be within a few tens of meters of the positions used for the first survey moment, so that the measured data are highly reproducible. The exact allowable distance between the first and the subsequently repeated positions of the receiver depends on subsurface electrical parameters and the source frequencies used to probe the earth's structure. Typically, the allowable distance is less than 100 m for probe frequencies of 0.25Hz, for a reservoir 1500 m below the seabed, with a horizontal resistivity of the bottom of the earth of 1.0 Ohm-m, and an EVTI = 2.0.

[0036] The individual data processing steps applied in the present method, for online and offline electric and magnetic field data, both at the first lifting moment and at the most lifting moment, are

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15/28 standard procedures used by offshore CSEM survey practitioners and described in the prior art, including the publications referred to herein. Several additional steps may be advisable to prepare the measured data acquired at the beginning and later times of the survey, for mathematical inversion, depending on the quality, spatial coverage, and other aspects of the data (step 62 in the flowchart of Fig. 6). These additional steps may include: noise suppression using silencing or filtering in the source-receiver compensation domain, phase adjustments to consider large changes due to timing errors, amplitude adjustments to consider inconsistencies between components and sums of data to produce openings greater effective numbers (see, for example, US patent publication 2003 / 0050759A1). [0037] In the 2005 SEG work previously mentioned, Srnka reveals that the resistivity of an underwater reservoir can be converted into an image using CSEM data input for a three-dimensional (3D) inversion algorithm operating on a computer, in which, a priori, restrictions can be applied and the absolute values of the subsurface resistivity are determined. Thompson, et al. (Sensitivity to hydrocarbon targets using marine active source EM sounding: Diffusive EM imaging methods, EAGE Annual Meeting, Paris, June 2004) show an example of approximate image formation of marine CSEM data using a two-dimensional (2D) computer algorithm, which estimates only the contrasts of relative resistivity between terrestrial electrical structures, instead of determining values of absolute resistivity as is done, using nonlinear inversion. Carazzone, et al. (Three dimensional imaging of marine CSEM data, Extended Abstract, EM 3.3, SEG Annual Meeting, Houston, Texas, November 2005) show several examples of 3D inversion of nonlinear marine CSEM data, which roughly matched the resistivity values of the reservoir, measured by well induction profiles, in the reservoirs: However, none of these inversion examples explains the incorporation of EVTI in the results, nor does it explain the changes in image formation, dependent on time, in the resistivity of the reservoir.

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16/28 [0038] The methods of inversion of this invention for data acquired at each survey moment include, but are not limited to, four complementary approaches presented in PCT patent publication W02006 / 135510, which are summarized in the following paragraphs. In step 63 of the flowchart of Fig. 6, an inversion method is selected.

(1) (Step 64) 1D, 2D, and / or 3D iterative frontal modeling on a digital computer, using algorithms for isotropic terrestrial calculations well known to practitioners of the technique, including those referred to here, are compared with the modeling responses (amplitudes and / or phases), and the model is subsequently adjusted to match the actual field data with the modeled responses. In this method of isotropic interpretation, if HED data are to be used, in-line responses are modeled using vertical electrical resistivity, and out-of-line responses are modeled using horizontal resistivity, and the reverse, if HMD data has to be used. (See table 1 below.) Iterative adjustments for the vertical resistivity model are made by comparing them to the measured data for an EM field component that is only preferably sensitive, but, at least predominantly, to the vertical resistivity, and correspondingly , for the horizontal resistivity model. Where offline data is used, the data is preferably from receivers exactly at the source hull (ie at x = 0 in Fig. I). The ratio of inline model results to offline ones (resistivity versus depth z and location x, y) then provides one of the approximate terrestrial resistivity value including EVTI as a function of depth and position.

(2) (Step 65) 1D, 2D, and / or 3D iterative frontal modeling on a digital computer, using algorithms for anisotropic terrestrial calculations that include EVTI, well known to practitioners of the technique, including the work previously mentioned by Yin and Maurer, in which real data (amplitudes and / or phases) are compared with model responses (amplitudes and / or phases), the model being subsequently adjusted to combine the real field data with the modeled responses. In this anisotropic interpretation method, the responses in

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17/28 line and line are modeled simultaneously using estimates of both vertical and horizontal resistivity. The final model solution then contains terrestrial resistivities and the EVTI value (quantity) as a function of depth and lateral position.

(3) (Step 66) Mathematical inversion (image formation) 1D, 2D, and / or 3D automated identification on a digital computer, using isotropic resistivity algorithms well known to practitioners of the technique (see, for example, Newman et al ., Three Dimensional Electromagnetics (Oristaglio and Spies, eds.) Soc. Expl. Geophysicists, Tulsa, 299-321 (1999)). In an embodiment of this isotropic inversion method, E _x in line and E _z in line, for a HED source (or, H _x in line and H _y out of line for a HMD source), and H _z outside line for an HED source (or, H _z in line for an HMD source), are entered separately in the inversion program which then uses numerical optimization algorithms to solve, separately, for quantity, depth, and lateral distribution horizontal and vertical resistivities whose electromagnetic responses best fit the observed seabed data. EVTI is then found to subsequently form the inverted to horizontal resistivity ratio at each depth and location. Thus, as with isotropic frontal modeling, one explanation is that an inversion solution uses electromagnetic field data that is more sensitive to vertical resistivity, while the other inversion solution uses data that is more sensitive to horizontal resistivity.

(4) (Step 67) Automated mathematical inversion programs (image formation), in a digital computer, using anisotropic 1D resistivity algorithms (see, for example, the work previously mentioned by Tompkins, et al.), And anisotropic extensions of finite difference algorithms of the 2D and 3D frequency domain and time domain, previously developed by practitioners of the technique (see, for example, Weiss, et al., Geophysics 67, 1104-1114 (2002); and Weiss, et al ., Geophysics 68, 922-930 (2003)). In this anisotropic inversion method, the online and offline responses are fed together in the

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18/28 inversion program, which then uses numerical optimization algorithms to solve for the quantity, depth, and lateral distribution of horizontal and vertical resistivities whose electromagnetic responses best fit the observed sea bed data.

[0039] Isotropic approaches require two separate computer operations for an iterative frontal modeling program or an inversion program. An operation involves data for at least one sensitive electromagnetic field component only, preferably, but at least predominantly horizontal resistivity and the output is a volume of horizontal resistivity data. The other operation involves data for at least one EM field component sensitive only to preferably, but at least predominantly vertical resistivity, and the output is a volume of vertical resistivity data. Anisotropic approaches feed all data in a single operation. The data can be for field components that are sensitive to both vertical and horizontal resistivity; however, the method produces mathematically more robust results if the data includes a component sensitive only to vertical resistivity, and another sensitive only to horizontal resistivity. Thus, a preferred set of electromagnetic data, for one approach, will be a preferred set for all approaches (for a given type of source). Table 1 lists sensitivities for vertical resistivity p _v and for horizontal resistivity Ph, or both, for both types of HED and HMD sources, and for in-line and off-line receiver locations. (Preferred offline data is from locations in the source code.) The entries in table 1, of greatest interest to the present invention, are those for which the data depends, at least predominantly, on p _v or Ph. It can be seen from table 1 and, from the previous description of the method, that all preferred embodiments of the invention require in-line measurement of at least one EM field component and offline measurement of at least one EM field component. Additional data provides the benefits of expected data redundancy In Table 1, the sensitivity labeled only for p _v or Ph, assumes a terrestrial model of

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19/28 flat stratification, and it has to be recognized that in real situations this sensitivity will not be so pure. It must be recognized that table 1 applies to offshore environments. Table 1 would have to be changed considerably for terrestrial applications.

[0040] Table 1

Marine CSEM data - EVTI responses Source Location of Receptor Dice Pv / Ph Sensitivity resistivity HED In line Ex Both (predominantly p _v ) (( (( Hy Both (predominantly p _v ) (( (( E _z> Just p _v (( (( E _y , H _x , H _z Theoretically = 0 HED Out of line Ex Both (predominantly Ph) (( (( Hy Both (predominantly Ph) (( (( H _z Ph only (( (( Ey, E _z , H _x Both (p _v and Ph mixed) HMD In line Ey Both (predominantly Ph) (( (( H _x Both (predominantly Ph) (( (( H _z Ph only (( (( Εχ, E _Z , Hy Theoretically = 0 HMD Out of line Ey Both (predominantly p _v ) (( (( H _x Both (predominantly p _v ) (( (( E _z Just p _v (( (( Εχ, Hy, H _z Both (p _v and Ph mixed)

[0041] The experienced practitioner will readily recognize that all of the above approaches, whether isotropic or anisotropic, frontal modeling or inversion, involve solving Maxwell's electromagnetic field equations by computer-aided numerical methods. With all known source acquisition parameters, along with background resistivities (salt water, etc.), and measured data for at least two EM field components, the only one

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Unknown is resistivity and it can be resolved.

[0042] Iterative frontal modeling approaches will typically be implemented on the computer, but typically require manual guidance. The data interpreter typically inserts known or estimated resistivity parameters in an initial depth model. This model may include, among other parameters, the depth of sea water, the resistivity of the water and its vertical gradient, the resistivity of the air, and a first assumption of terrestrial resistivity based on prior knowledge (for example, profiling of wells in a similar area), associated data (for example, seismic velocities converted into resistivity through statistical relationship), and general technology experience. Often, a uniform background resistivity value is chosen. The primary effect of the initial resistivity model is to accelerate or delay convergence. The model is then run on a computer using an algorithm that solves Maxwell's equations for the chosen input values and, as a result, synthetic data are obtained for the survey configuration corresponding to the actual data. The interpreter then compares the synthetic and real data in different locations and, based on the available knowledge of expected responses, modifies the resistivity in the model in order to bring the synthetic data closer to the real data. The process is typically repeated several times, until the criteria set by the interpreter are met, that is, the final resistivity-depth synthetic data of the model matches the actual data, within an accepted limit. If the process is not convergent, this typically means that the geology is complex, requiring that more frequency, source-receiver distances, and E or H components need to be examined or that the measured data is in some way corrupted.

[0043] In inversion approaches, the data interpreter builds a depth model of initial resistivity using known values (sea water, air, etc.) and an initial assumption for terrestrial resistivity, often considered to be uniform and representative of the area, as determined by experience, approximate values as described above for

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21/28 frontal modeling. The actual data is then entered into a computer algorithm along with the initial resistivity model, and the algorithm generates synthetic data by solving Maxwell's equations, which is typically done by numerical, iterative schemes, well known in the art. In the preferred embodiments of the invention, the algorithm uses mathematical techniques, such as gradients derived from the differences between real and synthetic data, to find changes in the model, which will result in minimizing the mismatch between real and synthetic data, in the next iteration of the process. The computer algorithm is capable of handling much more complexity in the data and model than a human interpreter, and it is allowed to continue to operate its internal iterative processing until the mismatch between real and synthetic data reaches a small, predetermined value. At this point, it is said that the mathematical response has converged on an optimal solution, which corresponds to a final resistivity-depth model that better represents the true structure of terrestrial resistivity including all hydrocarbons that are present.

[0044] A user of the present invention could, for example, select (step 63 of Fig. 6) an embodiment in which both iterative modeling and frequency domain inversion, as described herein, are used, but limited to computer programs and isotropic algorithms, to provide cross-checking of EVTI results (step 68) and also to better incorporate the interpreter's geological knowledge. The selected data could, for example, have been acquired using a controlled source of HED that was towed close to the seabed (preferably between 25 and 50 m) or placed in stationary positions on the seabed, between consecutive pairs of receivers on the seabed, along the source line. In this case, only in-line Ex and Ez electric field responses are needed, measured simultaneously only with offline responses, in a variety of online ranges: and offline, typically zero (0) to 12000 m in line, and one (1) at 8000 m offline, for an HED power (dipole moment) of 300000 A / m. Practitioners of the technique will understand that the choice of in-line and cross-line strips (outside

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22/28 line), that is, source-receiver distances, for these response measurements depend on the power of the source: and the frequencies used in the survey, which, in turn, depends on the expected horizontal and vertical resistivities and the depth of the target (s) of interest.

[0045] Alternative options to the table, 1 for measuring a field component sensitive to horizontal resistivity only exist in the form of passive source electromagnetic measurements: Measurement of electromagnetic response in the absence of a man-operated source is a known technique called survey magnetoteluric (MT). The published literature shows how to measure the resistivity of the earth, below the seabed, using the passive-source marine magnetoteluric method (MMT) (Constable et al., Geophysics 63, 816425 (1998); Hoversten et al., Geophysics 65, 1476-1488 (2000)). The source of energy for magnetoteluric is natural fluctuations in the magnetic field of the Earth's environment, due primarily to ionospheric fluctuations and lightning. MMT measurements are typically confined to horizontal magnetic and electric fields (E _x , E _y , H _x , H _y ), although vertical electric field data (E _z ) is sometimes useful for estimating lateral variations in geological structures (Zhdanov and Wan, Three-dimentional marine magnetotellurics for petroleum exploration, SEG 2003, Annual Meeting Expanded, 537-540 (2003)). Analyzes of these data produce information limited almost entirely to horizontal resistivity, [0046] The inversion calculation is performed for an initial survey and (step 61 in Fig. 6), for at least one survey performed at a later time (step 72 ).

[0047] The mathematical inversion of marine CSEM data provides a means to map resistivity in depth from relatively inexpensive measurements obtained remotely at or near the seabed. This resistivity map can then be used to estimate hydrocarbon saturation across the reservoir rock, using empirical relationships that connect resistivity to saturation, such as Archie's law (Archie, Trans. American Inst. Mech. Eng. 146, 54-62 (1942)). Estimates of rock and brine properties from seismic and

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23/28 well and, from other media such as physical rock models, can be used to calibrate or improve inversions.

[0048] It is well known to practitioners of the technique that electrical resistivity is a sensitive measure of the fluid content in porous rocks such as underground hydrocarbon reservoirs (Keller and Frischnecht, Electrical Methods in Geophysical Prospecting, 20-33, Pergamon (1966): The gross isotropic electrical resistivity of a wet rock is generally described by the empirical mathematical relationship known as Archie's law:

Pr = Pw (1-S _hc ) ^m .0- ^m (1) where Pr is the gross resistivity of the rock, p _w is the resistivity of the brine in the rock, Shc is the hydrocarbon saturation, Φ is the porosity, in is an empirical exponent that generally has an approximate value m = 2 and represents the rock matrix. Equation (1) models the rapid decrease in the gross resistivity of the reservoir when the hydrocarbon saturation decreases, for a given rock porosity and brine resistivity. When a hydrocarbon reservoir is producing, the porosity of the reservoir is essentially constant, unless the rock in the reservoir is inadvertently altered during production, for example, by diagenetic processes, such as clay growth. The reservoir could also be intentionally altered by chemical products, or pressure-fracturing processes, used to stimulate production. Information on the mass density of the rock can be obtained from seismic reflection data to subsequently estimate these changes in porosity. The resistivity of the reservoir's brine, which moistens the pore surfaces, is also approximately constant during hydrocarbon production, for most reservoirs, unless water or some water-soluble fluid is artificially injected into the reservoir to stimulate production . Consequently, if pore spaces contain primarily hydrocarbon and brine fluids, local changes in crude resistivity can be a direct measure of local changes in Shc hydrocarbon saturation. If p _r o is local crude resistivity and Shco is local hydrocarbon saturation. in a while

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24/28 initial to, ep _r i is the local gross resistivity and Sm, is the local hydrocarbon saturation at a later time ti, then, replacing these values in equation (1) gives:

Shc1 = 1- (1-ShcO). (Pri / p _r o) [0049] Equation (2) provides a simple way to estimate the change in Sh _C once the initial reservoir properties are determined. If another electrically resistive fluid is introduced into the reservoir, such as carbon dioxide (CO ₂ ) to stimulate production or to sequester carbon, the direct relationship between Sh _C θ Pr collapses. and a more complicated method should be used to estimate Shc (Hoversten et al., Pressure and fluid saturation prediction in a multi-component reservoir using combined seismic and electromagnetic imaging, Geophysics 68, 1580.1591, (2003)).

Examples [0050] In place of actual CSEM data of the type and combination required in this invention, numerical calculations employing 1D methods well known to those skilled in the art are used here to demonstrate the electromagnetic seabed responses used by the invention. Figure 2 shows the survey geometry and 1D resistivity model used to calculate the CSEM response data model. The layout of the equipment is the same as in fig. 1 (and the same reference numbers are applied), except that only one HED source is used. The model for this example uses a seawater depth of 3000 m and a simulated hydrocarbon reservoir 50 m thick 8, the top of which is buried 1000 m below the seabed. Figures 3A and 3B show the calculated changes in seabed field amplitudes in line E _x from a standard HED source (ie responses to a 1 m long dipole unit and 1A current) in volts / meter (fig. 3A) and the absolute phases (fig. 3B) caused by EVTI of varying magnitudes (EVTI / p _v : ph ratio from 1: 1 to 5: 1, where p _v is the vertical resistivity and Ph is the horizontal resistivity ), corresponding to the survey geometry and the terrestrial parameters of Fig. 2, for a sinusoidal source frequency of 0.25Hz. Anisotropy is found

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25/28 typically on the ground above and below the hydrocarbon layer, and may be present within the hydrocarbon layer if, for example, the reservoir is stratified. But, unless the hydrocarbon layer is thick enough to be resolved by the electromagnetic data, its EVTI effect is not large enough to be visible in these model data, and thus the reservoir is assumed to have isotropic resistivity for the purpose of these simulations. The HED is aligned in the x direction (sometimes referred to as an XED source). (It is typical in marine CSEM practice to align an HED source, which is basically a long cable, with the direction in which it is being towed, this is the orientation it naturally tends to take when towed by a cable connected to one end) . For this calculation the horizontal resistivity Ph is set to 1, OOhm-m. The horizontal axis is the distance x, along the source line, measured in terms of the distance from the source moving from a particular inline receiver, that is, one of the receivers 6, located along the towing cable of the source 5 (see Fig. 1). Practitioners of the technique will understand that other input parameter values could also be used, well, in this illustration. The reservoir layer 8 is assumed to have a resistivity of 100 Ohm-m (electrically isotropic, EVTI = 1). Six curves show responses from seabed receptors for several cases with reservoir 8 present or not, and for variable values of EVTI of the cover _: and underlying layers. In figs. 3 AB, the second digit in the reference number denotes the EVTI value and, if the reservoir layer is present (WR) in the model, or is not present (“NR”) according to the following explanation: 1 denotes EVTI = pv / ph = 1, WR; 2 denotes EVTI = 2, WR; 3 denotes EVTI = 5, WR; 4 denotes EVTI = 1, NR; 5 denotes EVTI = 2, NR; and 6 denotes EVTI = 5, NR. It can be seen that when the effect of EVTI increases the presence or absence of the target layer progressively makes less difference, which illustrates the need for the present invention when determining changes in the properties of the reservoir.

[0051] Figures 4 and 5 are horizontal slices of a 3D depth map as can be prepared (inverting data associated with different frequencies)

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26/28 as indicated in step 69 of fig. 6. Figure 4 shows a 3D simulated anisotropic inversion of online and offline data collected in the initial moment using the survey geometry of Fig. 2, over an underground hydrocarbon reservoir. Neither Fig. 4 nor 5 has been prepared by actual inversion data; they are merely intended illustrations to indicate the types of resistivity maps [69] and time-dependent comparisons [73] that could be made using the method of the present invention. Unlike the case of a simple, uniform layer model, shown in figures 1 and 2, here, the hydrocarbon saturation and the thickness of the profitable zone vary within the reservoir layer due to its geological structure and internal properties, so that the reservoir resistivity varies laterally. The locations of simulated wells 9 for producing hydrocarbons are shown. The contours represent the values of the inverted vertical resistivity calculated for the average of 50 m of gross reservoir thickness (numerical values in Ohm-m units are indicated by the gray scale of the reference bar) measured independently of seismic and well data. The average vertical resistivity: it is typically the most robust parameter in these inversions. For a good first approach, the data collected online and offline are, primarily, sensitive to the vertical thickness-resistivity product, in the depth of the reservoir. In this simulation, a high fluid permeability zone is indicated by the dashed line 41. Other reference numbers have the same meanings as in Fig. 1 [0052] Figure 5 shows a 3D simulated anisotropic inversion of collected online and offline data at a later time than shown for the results in Fig. 4, again, using the survey geometry of figure 2. In this simulated result, the source and locations of the receivers for the survey at the later time are shown exactly in the same positions as for the initial survey. In practice, small errors can be introduced in the inversion of subsurface resistivity for the survey (s) later, if the source and the locations of the

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27/28 receivers are very far from those used in the survey at the initial moment, for example, greater than 100 m.

[0053] The contours in Fig. 5 represent the values of inverted vertical resistivity with a calculated average for the 50 m thickness of the reservoir, corresponding to the measured sea bed CSEM data at a later time. In the simulated result, the average vertical resistivity within the reservoir model is reduced substantially near the high permeability zone of the fluid (ie, the darker areas have shrunk in size), as would be expected in a real reservoir, since, the Average local resistivity is reduced by displacement of electrically resistive hydrocarbons. Depending on the actual values of the porosity of the rock, permeability, and initial fluid saturation of a real reservoir and the rates of hydrocarbon production from two wells, the time between the first resistivity image (Fig. 4) and the second resistivity image in Fig. 5 it could typically be 3 to 10 years. [0054] It will be clear from the description of this invention that repeated surveys can be acquired in a variety of moments after the survey of the initial moment, depending on the expected production rates, and the resistivity inversion performed appropriately for one or more moments later and then compared with inversion for the initial moment or inversion of resistivity for one or more moments later of the mentioned surveys.

[0055] A further embodiment of the present invention uses values of inverted resistivity at the initial moment 1, and at the last moment later 2, to estimate (step 70 of Fig. 6) the average hydrocarbon saturations Shd and Sh _C 2 in these two moments, and then map (step 71) and analyze (step 73) the time-dependent changes in saturation AShc = (Shd - Sh _C 2) within the reservoir area. The conversion of resistivity to fluid saturation is well known to practitioners of the technique, and can be performed in the various ways described in the prior art, including the use of empirical relationships such as Archie's law, calibrated for measurements of reservoir and saturation porosity. of water

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28/28 measured by well profiling.

[0056] Frequency domain or time domain techniques can be used for data acquisition, processing, analysis, and interpretation when practicing the method of the present invention. The choice between time domain and frequency domain techniques are mainly determined by operational considerations (such as water depth) that are well understood by practitioners of the technique. The sources, seabed instruments, and electric and magnetic field sensors required for the measured seabed data used in this invention are also well known to practitioners of offshore CSEM surveys. The instruments and sensors were originally developed for offshore magnetoteluric surveys (Chave et al., Electrical Exploration Methods for the Seafloor ”, Electromagnetic Methods in Applied Geophysics, 2, 931-956, Society of Exploration Geophysicists, Tulsa (1991)).

[0057] The foregoing application is directed to particular embodiments of the present invention for the purpose of illustrating it. It will be apparent, however, to someone skilled in the art, that many modifications and variations to the embodiments described herein are possible. All of these modifications and variations are intended to be within the scope of the present invention, as defined in the appended claims.

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Claims (19)

1. Method for determining time-dependent changes in the hydrocarbon content of a subsurface reservoir from electromagnetic survey data from a controlled source obtained from the subsurface region containing the reservoir, characterized by the fact that it comprises: (a) obtaining electromagnetic field data recorded in a plurality of receiver locations online and offline (in relation to a survey source line) from an initial survey of the subsurface region, and corresponding survey results at least one further survey of the same region conducted under substantially the same conditions, said data comprising a combination of field component and sensitive receptor location, at least predominantly to vertical resistivity and a combination of field component and sensitive receptor location , at least predominantly, horizontal resistivity; where the aforementioned combination depends on an electromagnetic field design; (b) for each survey, solve Maxwelll's electromagnetic field equations for horizontal resistivity and vertical resistivity in a plurality of positions (x, y, z) in the subsurface reservoir, using survey acquisition parameters and field data electromagnetic measured; and (c) compare resistivity results calculated between the surveys, in which (d) the survey data comes from surveys that use a horizontal electric dipole electromagnetic source or a horizontal magnetic dipole electromagnetic source, (i) for the source of horizontal electric dipole, the combination of field component and receiver location being at least predominantly sensitive to vertical resistivity is vertical electric field component E _z in line and the combination of field component and sensitive receiver location at least predominantly to resistivity horizontal is a component of vertical magnetic field H _z offline; or Petition 870180054335, of 6/25/2018, p. 39/45 2/4 (ii) for the horizontal magnetic dipole source, the combination of field component and receiver location being sensitive at least predominantly to vertical resistivity is vertical electric field component E _z out of line and the combination of field component and location of sensitive receiver at least predominantly horizontal resistivity is a component of vertical magnetic field H _z in line; (e) the electromagnetic field equations are solved using the electromagnetic field data measured as known quantities and inverting the field equations by an iterative numerical method to converge on a resistivity model of the subsurface region. 2. Method according to claim 1, characterized by the fact that it additionally comprises, after calculating horizontal and vertical resistivities: calculate fluid saturation values from the calculated horizontal and vertical resistivities. 3. Method according to claim 2, characterized by the fact that the fluid saturation calculation uses Archie's law. 4. Method according to claim 1, characterized by the fact that the degree of duplication of survey geometry from one survey to another depends on subsurface electrical parameters and the frequency spectrum of the controlled source. 5. Method according to claim 4, characterized in that the receiver locations from one survey to another vary by no more than 100 meters. 6. Method according to claim 1, characterized in that the survey data come from surveys using an electromagnetic source of horizontal electric dipole. 7. Method according to claim 1, characterized in that the survey data come from surveys using a horizontal magnetic dipole electromagnetic source. 8. Method according to claim 1, characterized by the fact that the Petition 870180054335, of 6/25/2018, p. 40/45 3/4 electromagnetic field equations to be solved for electromagnetic field component values using a resistivity model assumed from the subsurface region and space above it, compare the calculated values of field components with measured values, adjust the values of model resistivity to compensate for any difference, and repeat the process until agreement is obtained within a predetermined criterion. 9. Method according to claim 8, characterized in that the model is isotropic (resistivity independent of the current flow direction), and the model is rotated twice each iteration, once assuming only the horizontal resistivity (vertical resistivity = 0), and once assuming only vertical resistivity (horizontal resistivity = 0). 10. Method according to claim 9, characterized in that the electromagnetic source is a horizontal electric dipole, and the model assuming only vertical resistivity is rotated using E _z data in line and the model assuming only horizontal resistivity is rotated using H _z data out of line 11. Method according to claim 9, characterized in that the electromagnetic source is a horizontal magnetic dipole, and the model assuming only vertical resistivity is rotated using E _z data offline and the model assuming only horizontal resistivity is rotated using H data _z online. 12. Method according to claim 8, characterized in that the model is anisotropic (resistivity depends on the current flow direction) and the model is rotated once every iteration. 13. Method according to claim 1, characterized in that the resistivity model is assumed to be isotropic. 14. Method according to claim 1, characterized in that the resistivity model is assumed to be anisotropic. 15. Method according to claim 1, characterized in that the method is implemented by computer and still comprises computing differences or resistivity relationships between the resistivity results of two surveys, position-by-position, and Petition 870180054335, of 6/25/2018, p. 41/45 4/4 to issue the differences or relations, or to store them in the computer's memory. 16. Method according to claim 1, characterized by the fact that the method is implemented by computer, and the comparison step comprises issuing or displaying a bi or three-dimensional map of resistivity values for each survey and then determining any increase or decrease from the initial survey to a later survey in size of a portion of the reservoir defined by having a resistivity value greater or less than a pre-selected value, or within a pre-selected range of resistivity values. 17. Method according to claim 2, characterized in that it additionally comprises determining the movement of hydrocarbon fluid occurring in the sub-surface region between the moment of the initial survey and the moment of at least a subsequent survey, the aforementioned determination being based in the fluid saturation values calculated from the different surveys. 18. Method according to claim 1, characterized by the fact that all electromagnetic field data for each survey is generated using a single source of electromagnetic survey that produces both vertical and horizontal currents. 19. Method according to claim 1, characterized by the fact that the recorded electromagnetic survey data obtained in (a) and used in (b) consist of one or more electromagnetic field components sensitive at least predominantly to vertical resistivity and a or more electromagnetic field components sensitive at least predominantly to horizontal resistivity. Petition 870180054335, of 6/25/2018, p. 42/45